Overexpression of IGFBP2 mRNA predicts poor survival in patients with glioblastoma

Transforming agents: The power of structural modifications in glioblastoma multiforme therapy

Glioblastoma (GBM) is a very deadly type of brain tumor with a poor prognosis and a short survival rate. Recent advancements in understanding GBM's molecular and genetic characteristics have led to the development of various therapeutic and diagnostic strategies. Key elements such as microRNAs, lncRNAs, exosomes, angiogenesis, and chromatin modifications are highlighted, alongside significant epigenetic alterations that impact therapy and diagnosis. Despite these advancements, molecular classifications have not improved patient outcomes due to intratumoral diversity complicating targeted therapies. In this article, it is tried to emphasize the potential of investigating the epigenetic landscape of GBM, particularly identifying patients with diffuse hypermethylation at gene promoters associated with better outcomes. Integrating epigenetic and genetic data has enhanced the identification of glioma subtypes with high diagnostic precision. The reversibility of epigenetic changes offers promising therapeutic prospects, as recent insights into the "epigenetic orchestra" suggest new avenues for innovative treatment modalities for this challenging cancer. In this review article, we focus on the roles of translational elements and their alterations in the context of GBM diagnosis and therapy.

Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM

BACKGROUND

Previous studies have described sex-specific patient subtyping in glioblastoma. The cluster labels associated with these "legacy data" were used to train a predictive model capable of recapitulating this clustering in contemporary contexts.

METHODS

We used robust ensemble machine learning to train a model using gene microarray data to perform multi-platform predictions including RNA-seq and potentially scRNA-seq.

RESULTS

The engineered feature set was composed of many previously reported genes that are associated with patient prognosis. Interestingly, these well-known genes formed a predictive signature only for female patients, and the application of the predictive signature to male patients produced unexpected results.

CONCLUSIONS

This work demonstrates how annotated "legacy data" can be used to build robust predictive models capable of multi-target predictions across multiple platforms.

Identification and Verification of Key Genes Associated with Temozolomide Resistance in Glioblastoma Based on Comprehensive Bioinformatics Analysis

Background

Glioblastoma (GBM) is the most aggressive form of brain cancer, with poor prognosis despite treatments like temozolomide (TMZ). Resistance to TMZ is a significant clinical challenge, and understanding the genes involved is crucial for developing new therapies and prognostic markers. This study aims to identify key genes associated with TMZ resistance in GBM, which could serve as valuable biomarkers for predicting patient outcomes and potential targets for treatment.

Objectives

This study aimed to identify genes involved in TMZ resistance in GBM and to assess the value of these genes in GBM treatment and prognosis evaluation.

Materials and Methods

Bioinformatics analysis of Gene Expression Omnibus (GEO) datasets (GSE113510 and GSE199689) and The Chinese Glioblastoma Genome Atlas (CGGA) database was performed to identify differentially expressed genes (DEGs) between GBM cell lines with and without TMZ resistance. Subsequently, the key modules associated with GBM patient prognosis were identified by weighted gene coexpression network analysis (WGCNA). Furthermore, hub genes related to TMZ resistance were accurately screened and confirmed using three machine learning algorithms. In addition, immune cell infiltration analysis, TF-miRNA coregulatory network analysis, drug sensitivity prediction, and gene set enrichment analysis (GSEA) were also performed for temozolomide resistance-specific genes. Finally, the expression levels of key genes were validated in our constructed TMZ-resistant cell lines by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting (WB).

Results

Integrated analysis of the GEO and CGGA datasets revealed 769 differentially expressed genes (DEGs), comprising 350 downregulated and 419 upregulated genes, between GBM patients and normal controls. Among these DEGs, three key genes, namely, PITX1, TNFRSF11B, and IGFBP2, exhibited significant differences in expression between groups and were prioritized via machine learning algorithms. The expression levels of these genes were found to be closely related to adverse clinical features and immune cell infiltration levels in GBM patients. These genes were also found to participate in several biological pathways and processes. RT‒qPCR and WB confirmed the differential expression of these genes in vitro, indicating that they play vital roles in GBM patients with TMZ resistance.

Conclusions

PITX1, TNFRSF11B, and IGFBP2 are key genes associated with the prognosis of GBM patients with TMZ resistance. The differential expression of these genes correlates with adverse outcomes in GBM patients, suggesting that they are valuable biomarkers for predicting patient prognosis and that they could serve as diagnostic biomarkers or treatment targets.

SVIP reduces IGFBP-2 expression and inhibits glioblastoma progression via stabilizing PTEN

Glioblastoma (GBM) presents significant challenges due to its invasive nature and genetic heterogeneity. In this study, we investigated the impact of Small VCP/P97-Interacting Protein (SVIP) on GBM progression. Our results revealed elevated expression of Insulin-like Growth Factor Binding Protein 2 (IGFBP-2) and STIP1 homology and U-box containing protein 1 (STUB1), coupled with reduced SVIP levels in GBM samples. Notably, high IGFBP-2 expression correlated with poor prognosis. Mechanistically, SVIP competitively inhibited STUB1, selectively binding to VCP/p97, thereby reducing PTEN degradation. This SVIP-mediated regulation exerted influence on the PTEN/PI3K/AKT/mTOR pathway, leading to the suppression of GBM progression. Co-localization experiments demonstrated that SVIP hindered PTEN ubiquitination and degradation by outcompeting STUB1 for VCP/p97 binding. Moreover, SVIP overexpression resulted in reduced activation of AKT/mTOR signaling and facilitated autophagy. In vivo experiments using a GBM xenograft model substantiated the tumor-suppressive effects of SVIP, evident by suppressed tumor growth, decreased IGFBP-2 expression, and improved survival rates. Collectively, our findings underscore the functional significance of SVIP in GBM progression. By inhibiting STUB1 and stabilizing PTEN, SVIP modulates the expression of IGFBP-2 and attenuates the activation of the PI3K/AKT/mTOR pathway, thereby emerging as a promising therapeutic target for GBM treatment.

Age-Related Increases in IGFBP2 Increase Melanoma Cell Invasion and Lipid Synthesis

Aged patients with melanoma (>65 years old) have more aggressive disease relative to young patients (<55 years old) for reasons that are not completely understood. Analysis of the young and aged secretome from human dermal fibroblasts identified >5-fold levels of IGF-binding protein 2 (IGFBP2) in the aged fibroblast secretome. IGFBP2 functionally triggers upregulation of the PI3K-dependent fatty acid biosynthesis program in melanoma cells. Melanoma cells co-cultured with aged dermal fibroblasts have higher levels of lipids relative to those co-cultured with young dermal fibroblasts, which can be lowered by silencing IGFBP2 expression in fibroblasts prior to treating with conditioned media. Conversely, ectopically treating melanoma cells with recombinant IGFBP2 in the presence of conditioned media from young fibroblasts or overexpressing IGFBP2 in melanoma cells promoted lipid synthesis and accumulation in melanoma cells. Treatment of young mice with rIGFBP2 increases tumor growth. Neutralizing IGFBP2 in vitro reduces migration and invasion in melanoma cells, and in vivo studies demonstrate that neutralizing IGFBP2 in syngeneic aged mice reduces tumor growth and metastasis. Our results suggest that aged dermal fibroblasts increase melanoma cell aggressiveness through increased secretion of IGFBP2, stressing the importance of considering age when designing studies and treatment.

SIGNIFICANCE

The aged microenvironment drives metastasis in melanoma cells. This study reports that IGFBP2 secretion by aged fibroblasts induces lipid accumulation in melanoma cells, driving an increase in tumor invasiveness. Neutralizing IGFBP2 decreases melanoma tumor growth and metastasis.

Expression and prognostic significance of microsomal triglyceride transfer protein in brain tumors: a retrospective cohort study

Background

Glioblastoma (GBM) is the most common malignant brain tumor and has poor survival. An elevated cholesterol level is involved occurrence and progression of brain tumors. Microsomal triglyceride transfer protein (MTTP) is a target for lowering lipids, and its inhibition helps to improve hyperlipidemia. However, whether the altered expression of MTTP affects the development and prognosis of brain tumors is currently unidentified. The purpose of this study is to determine MTTP as a prognostic marker for brain tumors.

Methods

Data for patients with brain cancers and control brain tissue were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The datasets were analyzed using Mann-Whitney U-test or t-test to compare the expression of MTTP in normal and brain tumor tissues. To examine whether MTTP affected the prognosis of patients with brain tumors, log-rank test and multivariable Cox proportional hazard regression were conducted.

Results

The expression of MTTP was significantly upregulated in brain tumors and was correlated with age, tumor stage, and isocitrate dehydrogenase (IDH) mutation. Importantly, increased MTTP expression in brain tumors is associated with poor patient survival.

Conclusions

High MTTP expression is associated with brain tumor development, tumor stage, and prognosis. Therefore, MTTP is an independent prognostic indicator for brain tumors, which can serve as one of the possible targets for adjuvant treatment of GBM.

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses

BACKGROUND

Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM.

METHODS

A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023.

RESULTS

From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts.

CONCLUSION

We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

Identification of Hypoxia Prognostic Signature in Glioblastoma Multiforme Based on Bulk and Single-Cell RNA-Seq

Glioblastoma (GBM) represents a profoundly aggressive and heterogeneous brain neoplasm linked to a bleak prognosis. Hypoxia, a common feature in GBM, has been linked to tumor progression and therapy resistance. In this study, we aimed to identify hypoxia-related differentially expressed genes (DEGs) and construct a prognostic signature for GBM patients using multi-omics analysis. Patient cohorts were collected from publicly available databases, including the Gene Expression Omnibus (GEO), the Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas-Glioblastoma Multiforme (TCGA-GBM), to facilitate a comprehensive analysis. Hypoxia-related genes (HRGs) were obtained from the Molecular Signatures Database (MSigDB). Differential expression analysis revealed 41 hypoxia-related DEGs in GBM patients. A consensus clustering approach, utilizing these DEGs' expression patterns, identified four distinct clusters, with cluster 1 showing significantly better overall survival. Machine learning techniques, including univariate Cox regression and LASSO regression, delineated a prognostic signature comprising six genes (ANXA1, CALD1, CP, IGFBP2, IGFBP5, and LOX). Multivariate Cox regression analysis substantiated the prognostic significance of a set of three optimal signature genes (CP, IGFBP2, and LOX). Using the hypoxia-related prognostic signature, patients were classified into high- and low-risk categories. Survival analysis demonstrated that the high-risk group exhibited inferior overall survival rates in comparison to the low-risk group. The prognostic signature showed good predictive performance, as indicated by the area under the curve (AUC) values for one-, three-, and five-year overall survival. Furthermore, functional enrichment analysis of the DEGs identified biological processes and pathways associated with hypoxia, providing insights into the underlying mechanisms of GBM. Delving into the tumor immune microenvironment, our analysis revealed correlations relating the hypoxia-related prognostic signature to the infiltration of immune cells in GBM. Overall, our study highlights the potential of a hypoxia-related prognostic signature as a valuable resource for forecasting the survival outcome of GBM patients. The multi-omics approach integrating bulk sequencing, single-cell analysis, and immune microenvironment assessment enhances our understanding of the intricate biology characterizing GBM, thereby potentially informing the tailored design of therapeutic interventions.

METTL3-mediated HOTAIRM1 promotes vasculogenic mimicry icontributionsn glioma via regulating IGFBP2 expression

BACKGROUND

HOTAIRM1 is revealed to facilitate the malignant progression of glioma. Vasculogenic mimicry (VM) is critically involved in glioma progression. Nevertheless, the molecular mechanism of HOTAIRM1 in regulating glioma VM formation remains elusive. Thus, we attempted to clarify the role and mechanism of HOTAIRM1 in VM formation in glioma.

METHODS

qRT-PCR and western blot assays were used to evaluate the gene and protein expression levels of HOTAIRM1 in glioma patient tissue samples and cell lines. The role of HOTAIRM1 in glioma cell progression and VM formation was explored using a series of function gain-and-loss experiments. RNA-binding protein immunoprecipitation (RIP), RNA pull-down, and mechanism experiments were conducted to assess the interaction between HOTAIRM1/METTL3/IGFBP2 axis. Furthermore, rescue assays were conducted to explore the regulatory function of HOTAIRM1/METTL3/IGFBP2 in glioma cell cellular processes and VM formation.

RESULTS

We found that HOTAIRM1 presented up-regulation in glioma tissues and cells and overexpression of HOTAIRM1 facilitated glioma cell proliferation, migration, invasion, and VM formation. Furthermore, overexpression of HOTAIRM1 promoted glioma tumor growth and VM formation capacity in tumor xenograft mouse model. Moreover, HOTAIRM1 was demonstrated to interact with IGFBP2 and positively regulated IGFBP2 expression. IGFBP2 was found to promote glioma cell malignancy and VM formation. Mechanistically, METTL3 was highly expressed in glioma tissues and cells and was bound with HOTAIRM1 which stabilized HOTAIRM1 expression. Rescue assays demonstrated that METTL3 silencing counteracted the impact of HOTAIRM1 on glioma cell malignancy and VM formation capacity.

CONCLUSION

HOTAIRM1, post-transcriptionally stabilized by METTL3, promotes VM formation in glioma via up-regulating IGFBP2 expression, which provides a new direction for glioma therapy.

Signaling Pathways of the Insulin-like Growth Factor Binding Proteins

The 6 high-affinity insulin-like growth factor binding proteins (IGFBPs) are multifunctional proteins that modulate cell signaling through multiple pathways. Their canonical function at the cellular level is to impede access of insulin-like growth factor (IGF)-1 and IGF-2 to their principal receptor IGF1R, but IGFBPs can also inhibit, or sometimes enhance, IGF1R signaling either through their own post-translational modifications, such as phosphorylation or limited proteolysis, or by their interactions with other regulatory proteins. Beyond the regulation of IGF1R activity, IGFBPs have been shown to modulate cell survival, migration, metabolism, and other functions through mechanisms that do not appear to involve the IGF-IGF1R system. This is achieved by interacting directly or functionally with integrins, transforming growth factor β family receptors, and other cell-surface proteins as well as intracellular ligands that are intermediates in a wide range of pathways. Within the nucleus, IGFBPs can regulate the diverse range of functions of class II nuclear hormone receptors and have roles in both cell senescence and DNA damage repair by the nonhomologous end-joining pathway, thus potentially modifying the efficacy of certain cancer therapeutics. They also modulate some immune functions and may have a role in autoimmune conditions such as rheumatoid arthritis. IGFBPs have been proposed as attractive therapeutic targets, but their ubiquity in the circulation and at the cellular level raises many challenges. By understanding the diversity of regulatory pathways with which IGFBPs interact, there may still be therapeutic opportunities based on modulation of IGFBP-dependent signaling.

Age-related increases in IGFBP2 increase melanoma cell invasion and lipid synthesis

Aged melanoma patients (>65 years old) have more aggressive disease relative to young patients (<55 years old) for reasons that are not completely understood. Analysis of the young and aged secretome from human dermal fibroblasts identified >5-fold levels of insulin-like growth factor binding protein 2 (IGFBP2) in the aged fibroblast secretome. IGFBP2 functionally triggers upregulation of the PI3K-dependent fatty acid biosynthesis program in melanoma cells through increases in FASN. Melanoma cells co-cultured with aged dermal fibroblasts have higher levels of lipids relative to young dermal fibroblasts, which can be lowered by silencing IGFBP2 expression in fibroblasts, prior to treating with conditioned media. Conversely, ectopically treating melanoma cells with recombinant IGFBP2 in the presence of conditioned media from young fibroblasts, promoted lipid synthesis and accumulation in the melanoma cells. Neutralizing IGFBP2 in vitro reduces migration and invasion in melanoma cells, and in vivo studies demonstrate that neutralizing IGFBP2 in syngeneic aged mice, ablates tumor growth as well as metastasis. Conversely, ectopic treatment of young mice with IGFBP2 in young mice increases tumor growth and metastasis. Our data reveal that aged dermal fibroblasts increase melanoma cell aggressiveness through increased secretion of IGFBP2, stressing the importance of considering age when designing studies and treatment.

Significance

The aged microenvironment drives metastasis in melanoma cells. This study reports that IGFBP2 secretion by aged fibroblasts induces FASN in melanoma cells and drives metastasis. Neutralizing IGFBP2 decreases melanoma tumor growth and metastasis.

Expression characteristics and their functional role of IGFBP gene family in pan-cancer

BACKGROUND

Insulin-like growth factor binding proteins (IGFBPs) are critical regulators of the biological activities of insulin-like growth factors. The IGFBP family plays diverse roles in different types of cancer, which we still lack comprehensive and pleiotropic understandings so far.

METHODS

Multi-source and multi-dimensional data, extracted from The Cancer Genome Atlas (TCGA), Oncomine, Cancer Cell Line Encyclopedia (CCLE), and the Human Protein Atlas (HPA) was used for bioinformatics analysis by R language. Immunohistochemistry and qRT-PCR were performed to validate the results of the database analysis results. Bibliometrics and literature review were used for summarizing the research progress of IGFBPs in the field of tumor.

RESULTS

The members of IGFBP gene family are differentially expressed in various cancer types. IGFBPs expression can affect prognosis of different cancers. The expression of IGFBPs expression is associated with multiple signal transduction pathways. The expression of IGFBPs is significantly correlated with tumor mutational burden, microsatellite instability, tumor stemness and tumor immune microenvironment. The qRT-PCR experiments verified the lower expression of IGFBP2 and IGFBP6 in gastric cancer and the lower expression of IGFBP6 in colorectal cancer. Immunohistochemistry validated a marked downregulation of IGFBP2 protein in gastric cancer tissues. The keywords co-occurrence analysis of IGFBP related publications in cancer showed relative research have been more concentrating on the potential of IGFBPs as tumor diagnostic and prognostic markers and developing cancer therapies.

CONCLUSIONS

These findings provide frontier trend of IGFBPs related research and new clues for identifying novel therapeutic targets for various cancers.

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Despite its growing use in cancer treatment, immunotherapy has been virtually ineffective in clinical trials for gliomas. The inherently cold tumor immune microenvironment (TIME) in gliomas, characterized by a high ratio of pro-tumor to anti-tumor immune cell infiltrates, acts as a seemingly insurmountable barrier to immunotherapy. Glioma stem cells (GSCs) within these tumors are key contributors to this cold TIME, often functioning indirectly through activation and recruitment of pro-tumor immune cell types. Furthermore, drivers of GSC plasticity and heterogeneity (e.g., reprogramming transcription factors, epigenetic modifications) are associated with induction of immunosuppressive cell states. Recent studies have identified GSC-intrinsic mechanisms, including functional mimicry of immune suppressive cell types, as key determinants of anti-tumor immune escape. In this review, we cover recent advancements in our understanding of GSC-intrinsic mechanisms that modulate GSC-TIME interactions and discuss cutting-edge techniques and bioinformatics platforms available to study immune modulation at high cellular resolution with exploration of both malignant (i.e., GSC) and non-malignant (i.e., immune) cell fractions. Finally, we provide insight into the therapeutic opportunities for targeting immunomodulatory GSC-intrinsic mechanisms to potentiate immunotherapy response in gliomas.

m6A regulator–mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in patients with intracranial aneurysms

Background

The role of epigenetic modulation in immunity is receiving increased recognition—particularly in the context of RNA N6-methyladenosine (m6A) modifications. Nevertheless, it is still uncertain whether m6A methylation plays a role in the onset and progression of intracranial aneurysms (IAs). This study aimed to establish the function of m6A RNA methylation in IA, as well as its correlation with the immunological microenvironment.

Methods

Our study included a total of 97 samples (64 IA, 33 normal) in the training set and 60 samples (44 IA, 16 normal) in the validation set to systematically assess the pattern of RNA modifications mediated by 22 m6A regulators. The effects of m6A modifications on immune microenvironment features, i.e., immune response gene sets, human leukocyte antigen (HLA) genes, and infiltrating immune cells were explored. We employed Lasso, machine learning, and logistic regression for the purpose of identifying an m6A regulator gene signature of IA with external data validation. For the unsupervised clustering analysis of m6A modification patterns in IA, consensus clustering methods were employed. Enrichment analysis was used to assess immune response activity along with other functional pathways. The identification of m6A methylation markers was identified based on a protein–protein interaction network and weighted gene co-expression network analysis.

Results

We identified an m6A regulator signature of IGFBP2, IGFBP1, IGF2BP2, YTHDF3, ALKBH5, RBM15B, LRPPRC, and ELAVL1, which could easily distinguish individuals with IA from healthy individuals. Unsupervised clustering revealed three m6A modification patterns. Gene enrichment analysis illustrated that the tight junction, p53 pathway, and NOTCH signaling pathway varied significantly in m6A modifier patterns. In addition, the three m6A modification patterns showed significant differences in m6A regulator expression, immune microenvironment, and bio-functional pathways. Furthermore, macrophages, activated T cells, and other immune cells were strongly correlated with m6A regulators. Eight m6A indicators were discovered—each with a statistically significant correlation with IA—suggesting their potential as prognostic biological markers.

Conclusion

Our study demonstrates that m6A RNA methylation and the immunological microenvironment are both intricately correlated with the onset and progression of IA. The novel insight into patterns of m6A modification offers a foundation for the development of innovative treatment approaches for IA.

Prognostic value of IGFBP2 in various cancers: a systematic review and meta-analysis

BACKGROUND

The prognostic significance of insulin-like growth factor binding protein 2 (IGFBP2) expression has been explored in plenty of studies in human cancers. Because of the controversial results, the meta-analysis was carried out to evaluate the relevance of IGFBP2 expression with the prognosis in various tumors.

METHODS

The data searched from four databases (Pubmed, Embase, Cochrane library, and Web of science) was used to calculate pooled hazard ratios (HRs) in this meta-analysis. Subgroup analyses were stratified by ethnicity, cancer type, publication year, Newcastle-Ottawa Scale score, treatments, and populations.

RESULTS

Twenty-one studies containing 5560 patients finally met inclusion criteria. IGFBP2 expression was associated with lower overall survival (HR = 1.57, 95% CI = 1.31-1.88) and progression-free survival (HR = 1.18, 95% CI = 1.04-1.34) in cancer patients, but not with disease-free survival (HR = 1.50, 95% CI = 0.91-2.46) or recurrence-free survival (HR = 1.50, 95% CI = 0.93-2.40). The subgroup analyses indicated IGFBP2 overexpression was significantly correlated with overall survival in Asian patients (HR = 1.42, 95% CI = 1.18-1.72), Caucasian patients (HR = 2.20, 95% CI = 1.31-3.70), glioma (HR = 1.36, 95% CI = 1.03-1.79), and colorectal cancer (HR = 2.52, 95% CI = 1.43-4.44) and surgery subgroups (HR = 1.97, 95% CI = 1.50-2.58).

CONCLUSION

The meta-analysis showed that IGFBP2 expression was associated with worse prognosis in several tumors, and may serve as a potential prognostic biomarker in cancer patients.

High expression of prolyl 4-hydroxylase subunit alpha-2 in lung adenocarcinoma indicates poor prognosis

OBJECTIVE

To analyze the Prolyl 4-Hydroxylase subunit Alpha-2 (P4HA2) expression in Lung Adenocarcinoma (LAUD).

METHODS

The authors assessed P4HA2 expression in the LUAD tumor ecosystem using single-cell analysis. The authors analyzed the relationship between P4HA2 expression and clinical features in LUAD and Brain Metastasis (BM) cases. The authors assessed the biological functions of P4HA2 using The Cancer Genome Atlas-LUAD dataset.

RESULTS

P4HA2 was more highly expressed in fibroblasts than in epithelial cells in normal lung and lung adenocarcinoma tissues (p < 0.001). P4HA2 was more highly expressed in malignant epithelial cells than in fibroblasts in the BM tissue (p = 0.002). P4HA2 expression was significantly higher in female cases than in male cases (p = 0.049) and was related to lymph node metastasis (p = 0.019) and a higher TNM stage (p = 0.020). High P4HA2 expression indicated a poor prognosis and served as an independent prognostic risk factor in lung cancer. P4HA2 was mainly enriched in the extracellular matrix organization, NADH regeneration, and canonical glycolysis. P4HA2 expression was negatively correlated with naive B cells, T-cells, CD8, and activated natural killer cells, but positively correlated with CD4 memory-activated T cells, regulatory T-cells, resting dendritic cells, and dendritic cell activation. P4HA2 messenger RNA expression was correlated with programmed death-ligand 1 and cytotoxic T-lymphocyte-associated protein 4.

CONCLUSION

P4HA2 is highly expressed in LUAD tumor cells, especially for the BM subtype, and is a valuable prognostic indicator of LUAD. It may be involved in a biological activity of distant metastasis of LUAD tumor cells and serve as a potential treatment target.

Prognostic impact of a lymphocyte activation-associated gene signature in GBM based on transcriptome analysis

Background

Glioblastoma multiforme (GBM) is a highly, malignant tumor of the primary central nervous system. Patients diagnosed with this type of tumor have a poor prognosis. Lymphocyte activation plays important roles in the development of cancers and its therapeutic treatments.

Objective

We sought to identify an efficient lymphocyte activation-associated gene signature that could predict the progression and prognosis of GBM.

Methods

We used univariate Cox proportional hazards regression and stepwise regression algorithm to develop a lymphocyte activation-associated gene signature in the training dataset (TCGA, n = 525). Then, the signature was validated in two datasets, including GSE16011 (n = 150) and GSE13041 (n = 191) using the Kaplan Meier method. Univariate and multivariate Cox proportional hazards regression models were used to adjust for clinicopathological factors.

Results

We identified a lymphocyte activation-associated gene signature (TCF3, IGFBP2, TYRO3 and NOD2) in the training dataset and classified the patients into high-risk and low-risk groups with significant differences in overall survival (median survival 15.33 months vs 12.57 months, HR = 1.55, 95% CI [1.28-1.87], log-rank test P < 0.001). This signature showed similar prognostic values in the other two datasets. Further, univariate and multivariate Cox proportional hazards regression models analysis indicated that the signature was an independent prognostic factor for GBM patients. Moreover, we determined that there were differences in lymphocyte activity between the high- and low-risk groups of GBM patients among all datasets. Furthermore, the lymphocyte activation-associated gene signature could significantly predict the survival of patients with certain features, including IDH-wildtype patients and patients undergoing radiotherapy. In addition, the signature may also improve the prognostic power of age.

Conclusions

In summary, our results suggested that the lymphocyte activation-associated gene signature is a promising factor for the survival of patients, which is helpful for the prognosis of GBM patients.

Highly expressed of SERPINA3 indicated poor prognosis and involved in immune suppression in glioma

Introduction

The prognosis of patients with glioma is dismal. It has been reported that Serpin peptidase inhibitor clade A member 3 (SERPINA3) is associated with the mobility and invasion of tumor cells. Our study was designed to explore the value of SERPINA3 messenger RNA (mRNA) expression in the biological process, prognosis, and immune significance in glioma.

Methods

We analyzed the biological functions of SERPINA3 through data from the Chinese Glioma Genome Atlas databases. Differentially expressed genes and enrichment analysis were performed and correlations between SERPINA3 expression and immune cell infiltration were analyzed. Further, we validated the expression and the survival prediction role of SERPINA3 by using tissue microarrays and RNAscope in situ hybridization in 321 gliomas. The correlations between the expression and clinical‐pathological parameters as well as other biomarkers were examined.

Results

Univariate and multivariate regression both indicated that the level of SERPINA3 transcript represented an independent prognostic factor. High levels of SERPINA3 correlated with poor survival in patients with glioma. Expression of SERPINA3 mRNA was observed positively correlated with MCM6, IGFBP2, and FKBP10. Enrichment analysis showed SERPINA3 mainly enriched in immune‐related terms and signaling pathways including MAPK, TNF, P53, PI3K‐Akt, nuclear factor‐κB. Immune infiltration analysis further declare the SERPINA3 expression negatively correlated with levels of Macrophages M1, native CD4⁺ T cell, monocytes, and Mast cell activated. And overexpression of SERPINA3 correlated with low CD4⁺ T cell infiltration in glioma tissues.

Conclusions

SERPINA3 may play a key role in the biological process of glioma cells especially in immune suppression activities. SERPINA3 may serve as an independent survival prediction factor in glioma patients.

The role of mRNA in the development, diagnosis, treatment and prognosis of neural tumors

Neural tumors can generally be divided into central nervous system tumors and peripheral nervous tumors. Because this type of tumor is located in the nerve, even benign tumors are often difficult to remove by surgery. In addition, the majority of neural tumors are malignant, and it is particular the same for the central nervous system tumors. Even treated with the means such as chemotherapy and radiotherapy, they are also difficult to completely cure. In recent years, an increasingly number of studies have focused on the use of mRNA to treat tumors, representing an emerging gene therapy. The use of mRNA can use the expression of some functional proteins for the treatment of genetic disorders or tissue repair, and it can also be applied to immunotherapy through the expression of antigens, antibodies or receptors. Therefore, although these therapies are not fully-fledged enough, they have a broad research prospect. In addition, there are many ways to treat tumors using mRNA vaccines and exosomes carrying mRNA, which have drawn much attention. In this study, we reviewed the current research on the role of mRNA in the development, diagnosis, treatment and prognosis of neural tumors, and examine the future research prospects of mRNA in neural tumors and the opportunities and challenges that will arise in the future application of clinical treatment.

Hub gene identification and prognostic model construction for isocitrate dehydrogenase mutation in glioma

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We identified ten hub genes which were driving IDH status in GBM and LGG.

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We constructed a prognostic model for IDH-mutant patients.

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Our findings have important clinical implications for accurate treatment in glioma.

Our study attempted to identify hub genes related to isocitrate dehydrogenase (IDH) mutation in glioma and develop a prognostic model for IDH-mutant glioma patients. In a first step, ten hub genes significantly associated with the IDH status were identified by weighted gene coexpression analysis (WGCNA). The functional enrichment analysis demonstrated that the most enriched terms of these hub genes were cadherin binding and glutathione metabolism. Three of these hub genes were significantly linked with the survival of glioma patients. 328 samples of IDH-mutant glioma were separated into two datasets: a training set (N = 228) and a test set (N = 100). Based on the training set, we identified two IDH-mutant subtypes with significantly different pathological features by using consensus clustering. A 31 gene-signature was identified by the least absolute shrinkage and selection operator (LASSO) algorithm and used for establishing a differential prognostic model for IDH-mutant patients. In addition, the test set was employed for validating the prognostic model, and the model was proven to be of high value in classifying prognostic information of samples. The functional annotation revealed that the genes related to the model were mainly enriched in nuclear division, DNA replication, and cell cycle. Collectively, this study provided novel insights into the molecular mechanism of IDH mutation in glioma, and constructed a prognostic model which can be effective for predicting prognosis of glioma patients with IDH-mutation, which might promote the development of IDH target agents in glioma therapies and contribute to accurate prognostication and management in IDH-mutant glioma patients.

Large-Scale Analysis Reveals Gene Signature for Survival Prediction in Primary Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive and common primary central nervous system tumour. Despite extensive therapy, GBM patients usually have poor prognosis with a median survival of 12–15 months. Novel molecular biomarkers that can improve survival prediction and help with treatment strategies are still urgently required. Here we aimed to robustly identify a gene signature panel for improved survival prediction in primary GBM patients. We identified 2166 differentially expressed genes (DEGs) using meta-analysis of microarray datasets comprising of 955 samples (biggest primary GBM cohort for such studies as per our knowledge) and 3368 DEGs from RNA-seq dataset with 165 samples. Based on the 1443 common DEGs, using univariate Cox and least absolute shrinkage and selection operator (LASSO) with multivariate Cox regression, we identified a survival associated 4-gene signature panel including IGFBP2, PTPRN, STEAP2 and SLC39A10 and thereafter established a risk score model that performed well in survival prediction. High-risk group patients had significantly poorer survival as compared with those in the low-risk group (AUC = 0.766 for 1-year prediction). Multivariate analysis demonstrated that predictive value of the 4-gene signature panel was independent of other clinical and pathological features and hence is a potential prognostic biomarker. More importantly, we validated this signature in three independent GBM cohorts to test its generality. In conclusion, our integrated analysis using meta-analysis approach maximizes the use of the available gene expression data and robustly identified a 4-gene panel for predicting survival in primary GBM.

Expanding the scope of candidate prognostic marker IGFBP2 in glioblastoma

Glioblastoma is the most common malignant brain tumor in adults. Unfortunately, it has a very poor prognosis and no cure. In a recent paper by Yuan et al. (Bioscience Reports (2019), DOI:10.1042/BSR20190045) RNAscope was used to detect insulin-like growth factor binding protein 2 (IGFBP2) mRNA in glioblastoma biopsies. The study revealed that patients with high levels of IGFBP2 mRNA had shorter survival and that IGFBP2 transcript level was an independent prognostic factor. It is also of value to determine the prognostic effect of IGFBP2 on established biomarkers such as isocitrate dehydrogenase (IDH1) mutations or telomerase reverse transcriptase (TERT) promoter mutation. In the present study, the combination of having a TERT promoter mutation, and at the same time a high level of IGFBP2 mRNA, was associated with very poor survival rates. It was concluded that IGFBP2 predicts the survival of the patients with TERT promoter mutation. This finding may have important implications for glioblastoma prognosis. IGFBP2 re-emerges as a candidate biomarker and potential therapeutic target in glioma. Further research into its functional roles during glioma progression may provide additional insights into this deadly disease.